Video contrast abnormity detection method and device
A contrast and anomaly technology, applied in the field of video contrast anomaly detection methods and devices, can solve problems such as low video contrast accuracy, and achieve the effects of improving accuracy and accurate detection results
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Embodiment 1
[0094] figure 2 It is a flowchart of a video contrast anomaly detection method provided in Embodiment 1 of the present invention, specifically including the following processing steps:
[0095] Step 201. Obtain a video image to be detected from the video to be detected.
[0096] Step 202, using a preset extraction method to extract brightness feature information of the video image to be detected.
[0097] Step 203: Match the brightness feature information with the first type of classification feature information to obtain a first matching result, wherein the first type of classification feature information is a plurality of high-contrast anomalies extracted in advance based on the preset extraction method The video image is determined corresponding to the obtained plurality of luminance characteristic information.
[0098] In this step, the SVM (Support Vector Machine) method can be used to determine the classification feature information. Specifically, the SVM method can b...
Embodiment 2
[0125] image 3 It is a flow chart of a video contrast anomaly detection method provided in Embodiment 2 of the present invention, specifically including the following processing steps:
[0126] Step 301. Obtain a video image to be detected from the video to be detected.
[0127] Step 302, using a preset extraction method to extract brightness feature information of the video image to be detected.
[0128] Step 303: Match the brightness feature information with the first type of classification feature information to obtain a first matching result, wherein the first type of classification feature information is a plurality of high-contrast anomalies extracted in advance based on the preset extraction method The video image is determined corresponding to the obtained plurality of luminance characteristic information.
[0129] In this step, the SVM method can be used to determine the classification feature information. Specifically, the SVM method can be used to analyze and tra...
Embodiment 3
[0144] Figure 4 It is a flowchart of a video contrast anomaly detection method provided in Embodiment 3 of the present invention, specifically including the following processing steps:
[0145] Step 401. Obtain a video image to be detected from the video to be detected.
[0146] Step 402: For each numerical value in the brightness value range, determine the number of pixels with the brightness value in the video image to be detected as the number of pixels corresponding to the numerical value.
[0147] Step 403, from all the values in the brightness value range, determine the maximum value and the minimum value corresponding to the number of pixels not less than the preset number threshold.
[0148] In this step, for the number of pixels G1 corresponding to each value within the brightness value range, compare the size relationship between G1 and the preset number threshold TH1. When G1 is less than TH1, set the value of G1 to 0. When G1 is not less than At TH1, the value...
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